\section{C\+V\+Base$<$ M\+L\+Algorithm, Mat\+Type, Predictions\+Type, Weights\+Type $>$ Class Template Reference}
\label{classmlpack_1_1cv_1_1CVBase}\index{C\+V\+Base$<$ M\+L\+Algorithm, Mat\+Type, Predictions\+Type, Weights\+Type $>$@{C\+V\+Base$<$ M\+L\+Algorithm, Mat\+Type, Predictions\+Type, Weights\+Type $>$}}


An auxiliary class for cross-\/validation.  


\subsection*{Public Types}
\begin{DoxyCompactItemize}
\item 
using \textbf{ M\+IE} = \textbf{ Meta\+Info\+Extractor}$<$ M\+L\+Algorithm, Mat\+Type, Predictions\+Type, Weights\+Type $>$
\begin{DoxyCompactList}\small\item\em A short alias for \doxyref{Meta\+Info\+Extractor}{p.}{classmlpack_1_1cv_1_1MetaInfoExtractor}. \end{DoxyCompactList}\end{DoxyCompactItemize}
\subsection*{Public Member Functions}
\begin{DoxyCompactItemize}
\item 
\textbf{ C\+V\+Base} ()
\begin{DoxyCompactList}\small\item\em Assert that M\+L\+Algorithm doesn\textquotesingle{}t take any additional basic parameters like num\+Classes. \end{DoxyCompactList}\item 
\textbf{ C\+V\+Base} (const size\+\_\+t num\+Classes)
\begin{DoxyCompactList}\small\item\em Assert that M\+L\+Algorithm takes the num\+Classes parameter and store it. \end{DoxyCompactList}\item 
\textbf{ C\+V\+Base} (const \textbf{ data\+::\+Dataset\+Info} \&dataset\+Info, const size\+\_\+t num\+Classes)
\begin{DoxyCompactList}\small\item\em Assert that M\+L\+Algorithm takes the num\+Classes parameter and a \doxyref{data\+::\+Dataset\+Info}{p.}{namespacemlpack_1_1data_aa243ad7e4d29363b858bbc92b732921d} parameter and store them. \end{DoxyCompactList}\item 
{\footnotesize template$<$typename... M\+L\+Algorithm\+Args$>$ }\\M\+L\+Algorithm \textbf{ Train} (const Mat\+Type \&xs, const Predictions\+Type \&ys, const M\+L\+Algorithm\+Args \&... args)
\begin{DoxyCompactList}\small\item\em Train M\+L\+Algorithm with given data points, predictions, and hyperparameters depending on what \doxyref{C\+V\+Base}{p.}{classmlpack_1_1cv_1_1CVBase} constructor has been called. \end{DoxyCompactList}\item 
{\footnotesize template$<$typename... M\+L\+Algorithm\+Args$>$ }\\M\+L\+Algorithm \textbf{ Train} (const Mat\+Type \&xs, const Predictions\+Type \&ys, const Weights\+Type \&weights, const M\+L\+Algorithm\+Args \&... args)
\begin{DoxyCompactList}\small\item\em Train M\+L\+Algorithm with given data points, predictions, weights, and hyperparameters depending on what \doxyref{C\+V\+Base}{p.}{classmlpack_1_1cv_1_1CVBase} constructor has been called. \end{DoxyCompactList}\end{DoxyCompactItemize}
\subsection*{Static Public Member Functions}
\begin{DoxyCompactItemize}
\item 
static void \textbf{ Assert\+Data\+Consistency} (const Mat\+Type \&xs, const Predictions\+Type \&ys)
\begin{DoxyCompactList}\small\item\em Assert there is the equal number of data points and predictions. \end{DoxyCompactList}\item 
static void \textbf{ Assert\+Weights\+Consistency} (const Mat\+Type \&xs, const Weights\+Type \&weights)
\begin{DoxyCompactList}\small\item\em Assert weighted learning is supported and there is the equal number of data points and weights. \end{DoxyCompactList}\end{DoxyCompactItemize}


\subsection{Detailed Description}
\subsubsection*{template$<$typename M\+L\+Algorithm, typename Mat\+Type, typename Predictions\+Type, typename Weights\+Type$>$\newline
class mlpack\+::cv\+::\+C\+V\+Base$<$ M\+L\+Algorithm, Mat\+Type, Predictions\+Type, Weights\+Type $>$}

An auxiliary class for cross-\/validation. 

It serves to handle basic non-\/data constructor parameters of a machine learning algorithm (like dataset\+Info or num\+Classes) and to assert that the machine learning algorithm and data satisfy certain conditions.

This class is not meant to be used directly by users. To cross-\/validate rather use end-\/user classes like \doxyref{Simple\+CV}{p.}{classmlpack_1_1cv_1_1SimpleCV} or \doxyref{K\+Fold\+CV}{p.}{classmlpack_1_1cv_1_1KFoldCV}.


\begin{DoxyTemplParams}{Template Parameters}
{\em M\+L\+Algorithm} & A machine learning algorithm. \\
\hline
{\em Mat\+Type} & The type of data. \\
\hline
{\em Predictions\+Type} & The type of predictions (labels/responses). \\
\hline
{\em Weights\+Type} & The type of weights. It supposed to be void$\ast$ when weights are not supported. \\
\hline
\end{DoxyTemplParams}


Definition at line 39 of file cv\+\_\+base.\+hpp.



\subsection{Member Typedef Documentation}
\mbox{\label{classmlpack_1_1cv_1_1CVBase_a8136390cdbea4d1b8b3fe885c223b590}} 
\index{mlpack\+::cv\+::\+C\+V\+Base@{mlpack\+::cv\+::\+C\+V\+Base}!M\+IE@{M\+IE}}
\index{M\+IE@{M\+IE}!mlpack\+::cv\+::\+C\+V\+Base@{mlpack\+::cv\+::\+C\+V\+Base}}
\subsubsection{M\+IE}
{\footnotesize\ttfamily using \textbf{ M\+IE} =  \textbf{ Meta\+Info\+Extractor}$<$M\+L\+Algorithm, Mat\+Type, Predictions\+Type, Weights\+Type$>$}



A short alias for \doxyref{Meta\+Info\+Extractor}{p.}{classmlpack_1_1cv_1_1MetaInfoExtractor}. 



Definition at line 44 of file cv\+\_\+base.\+hpp.



\subsection{Constructor \& Destructor Documentation}
\mbox{\label{classmlpack_1_1cv_1_1CVBase_a0b26728db400bc58a826f99965b22adc}} 
\index{mlpack\+::cv\+::\+C\+V\+Base@{mlpack\+::cv\+::\+C\+V\+Base}!C\+V\+Base@{C\+V\+Base}}
\index{C\+V\+Base@{C\+V\+Base}!mlpack\+::cv\+::\+C\+V\+Base@{mlpack\+::cv\+::\+C\+V\+Base}}
\subsubsection{C\+V\+Base()\hspace{0.1cm}{\footnotesize\ttfamily [1/3]}}
{\footnotesize\ttfamily \textbf{ C\+V\+Base} (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})}



Assert that M\+L\+Algorithm doesn\textquotesingle{}t take any additional basic parameters like num\+Classes. 

\mbox{\label{classmlpack_1_1cv_1_1CVBase_a0767da5bbe4ffe608d7a5887533bac41}} 
\index{mlpack\+::cv\+::\+C\+V\+Base@{mlpack\+::cv\+::\+C\+V\+Base}!C\+V\+Base@{C\+V\+Base}}
\index{C\+V\+Base@{C\+V\+Base}!mlpack\+::cv\+::\+C\+V\+Base@{mlpack\+::cv\+::\+C\+V\+Base}}
\subsubsection{C\+V\+Base()\hspace{0.1cm}{\footnotesize\ttfamily [2/3]}}
{\footnotesize\ttfamily \textbf{ C\+V\+Base} (\begin{DoxyParamCaption}\item[{const size\+\_\+t}]{num\+Classes }\end{DoxyParamCaption})}



Assert that M\+L\+Algorithm takes the num\+Classes parameter and store it. 


\begin{DoxyParams}{Parameters}
{\em num\+Classes} & Number of classes in the dataset. \\
\hline
\end{DoxyParams}
\mbox{\label{classmlpack_1_1cv_1_1CVBase_ad58931db3199d060bd4b5db9268197a5}} 
\index{mlpack\+::cv\+::\+C\+V\+Base@{mlpack\+::cv\+::\+C\+V\+Base}!C\+V\+Base@{C\+V\+Base}}
\index{C\+V\+Base@{C\+V\+Base}!mlpack\+::cv\+::\+C\+V\+Base@{mlpack\+::cv\+::\+C\+V\+Base}}
\subsubsection{C\+V\+Base()\hspace{0.1cm}{\footnotesize\ttfamily [3/3]}}
{\footnotesize\ttfamily \textbf{ C\+V\+Base} (\begin{DoxyParamCaption}\item[{const \textbf{ data\+::\+Dataset\+Info} \&}]{dataset\+Info,  }\item[{const size\+\_\+t}]{num\+Classes }\end{DoxyParamCaption})}



Assert that M\+L\+Algorithm takes the num\+Classes parameter and a \doxyref{data\+::\+Dataset\+Info}{p.}{namespacemlpack_1_1data_aa243ad7e4d29363b858bbc92b732921d} parameter and store them. 


\begin{DoxyParams}{Parameters}
{\em dataset\+Info} & Type information for each dimension of the dataset. \\
\hline
{\em num\+Classes} & Number of classes in the dataset. \\
\hline
\end{DoxyParams}


\subsection{Member Function Documentation}
\mbox{\label{classmlpack_1_1cv_1_1CVBase_ae1e254399d702b57b117cbf834faa45a}} 
\index{mlpack\+::cv\+::\+C\+V\+Base@{mlpack\+::cv\+::\+C\+V\+Base}!Assert\+Data\+Consistency@{Assert\+Data\+Consistency}}
\index{Assert\+Data\+Consistency@{Assert\+Data\+Consistency}!mlpack\+::cv\+::\+C\+V\+Base@{mlpack\+::cv\+::\+C\+V\+Base}}
\subsubsection{Assert\+Data\+Consistency()}
{\footnotesize\ttfamily static void Assert\+Data\+Consistency (\begin{DoxyParamCaption}\item[{const Mat\+Type \&}]{xs,  }\item[{const Predictions\+Type \&}]{ys }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [static]}}



Assert there is the equal number of data points and predictions. 

\mbox{\label{classmlpack_1_1cv_1_1CVBase_a5039acfc2b793e2dc813a07eddb457a1}} 
\index{mlpack\+::cv\+::\+C\+V\+Base@{mlpack\+::cv\+::\+C\+V\+Base}!Assert\+Weights\+Consistency@{Assert\+Weights\+Consistency}}
\index{Assert\+Weights\+Consistency@{Assert\+Weights\+Consistency}!mlpack\+::cv\+::\+C\+V\+Base@{mlpack\+::cv\+::\+C\+V\+Base}}
\subsubsection{Assert\+Weights\+Consistency()}
{\footnotesize\ttfamily static void Assert\+Weights\+Consistency (\begin{DoxyParamCaption}\item[{const Mat\+Type \&}]{xs,  }\item[{const Weights\+Type \&}]{weights }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [static]}}



Assert weighted learning is supported and there is the equal number of data points and weights. 

\mbox{\label{classmlpack_1_1cv_1_1CVBase_a31e9234a1f4e504d385dfa3870f71cad}} 
\index{mlpack\+::cv\+::\+C\+V\+Base@{mlpack\+::cv\+::\+C\+V\+Base}!Train@{Train}}
\index{Train@{Train}!mlpack\+::cv\+::\+C\+V\+Base@{mlpack\+::cv\+::\+C\+V\+Base}}
\subsubsection{Train()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}}
{\footnotesize\ttfamily M\+L\+Algorithm Train (\begin{DoxyParamCaption}\item[{const Mat\+Type \&}]{xs,  }\item[{const Predictions\+Type \&}]{ys,  }\item[{const M\+L\+Algorithm\+Args \&...}]{args }\end{DoxyParamCaption})}



Train M\+L\+Algorithm with given data points, predictions, and hyperparameters depending on what \doxyref{C\+V\+Base}{p.}{classmlpack_1_1cv_1_1CVBase} constructor has been called. 

\mbox{\label{classmlpack_1_1cv_1_1CVBase_ae50527d3c3f50b7a26eb239b6a3ed655}} 
\index{mlpack\+::cv\+::\+C\+V\+Base@{mlpack\+::cv\+::\+C\+V\+Base}!Train@{Train}}
\index{Train@{Train}!mlpack\+::cv\+::\+C\+V\+Base@{mlpack\+::cv\+::\+C\+V\+Base}}
\subsubsection{Train()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}}
{\footnotesize\ttfamily M\+L\+Algorithm Train (\begin{DoxyParamCaption}\item[{const Mat\+Type \&}]{xs,  }\item[{const Predictions\+Type \&}]{ys,  }\item[{const Weights\+Type \&}]{weights,  }\item[{const M\+L\+Algorithm\+Args \&...}]{args }\end{DoxyParamCaption})}



Train M\+L\+Algorithm with given data points, predictions, weights, and hyperparameters depending on what \doxyref{C\+V\+Base}{p.}{classmlpack_1_1cv_1_1CVBase} constructor has been called. 



The documentation for this class was generated from the following file\+:\begin{DoxyCompactItemize}
\item 
/var/www/mlpack.\+ratml.\+org/mlpack.\+org/\+\_\+src/mlpack-\/3.\+3.\+1/src/mlpack/core/cv/\textbf{ cv\+\_\+base.\+hpp}\end{DoxyCompactItemize}